/* Copyright 2018-2023 The TensorFlow Authors. All Rights Reserved.

Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at

    http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
=======================================================================*/

// This class has been generated, DO NOT EDIT!

package org.tensorflow.op.train;

import java.util.Arrays;
import org.tensorflow.GraphOperation;
import org.tensorflow.Operand;
import org.tensorflow.Operation;
import org.tensorflow.OperationBuilder;
import org.tensorflow.Output;
import org.tensorflow.op.Operands;
import org.tensorflow.op.RawOp;
import org.tensorflow.op.RawOpInputs;
import org.tensorflow.op.Scope;
import org.tensorflow.op.annotation.Endpoint;
import org.tensorflow.op.annotation.OpInputsMetadata;
import org.tensorflow.op.annotation.OpMetadata;
import org.tensorflow.op.annotation.Operator;
import org.tensorflow.proto.DataType;
import org.tensorflow.types.TString;
import org.tensorflow.types.family.TType;

/**
 * Restores a tensor from checkpoint files.
 * This is like {@code Restore} except that restored tensor can be listed as filling
 * only a slice of a larger tensor.  {@code shape_and_slice} specifies the shape of the
 * larger tensor and the slice that the restored tensor covers.
 * <p>The {@code shape_and_slice} input has the same format as the
 * elements of the {@code shapes_and_slices} input of the {@code SaveSlices} op.
 *
 * @param <T> data type for {@code tensor} output
 */
@OpMetadata(
    opType = RestoreSlice.OP_NAME,
    inputsClass = RestoreSlice.Inputs.class
)
@Operator(
    group = "train"
)
public final class RestoreSlice<T extends TType> extends RawOp implements Operand<T> {
  /**
   * The name of this op, as known by TensorFlow core engine
   */
  public static final String OP_NAME = "RestoreSlice";

  private Output<T> tensor;

  public RestoreSlice(Operation operation) {
    super(operation, OP_NAME);
    int outputIdx = 0;
    tensor = operation.output(outputIdx++);
  }

  /**
   * Factory method to create a class wrapping a new RestoreSlice operation.
   *
   * @param scope current scope
   * @param filePattern Must have a single element. The pattern of the files from
   * which we read the tensor.
   * @param tensorName Must have a single element. The name of the tensor to be
   * restored.
   * @param shapeAndSlice Scalar. The shapes and slice specifications to use when
   * restoring a tensors.
   * @param dt The type of the tensor to be restored.
   * @param options carries optional attribute values
   * @param <T> data type for {@code RestoreSlice} output and operands
   * @return a new instance of RestoreSlice
   */
  @Endpoint(
      describeByClass = true
  )
  public static <T extends TType> RestoreSlice<T> create(Scope scope, Operand<TString> filePattern,
      Operand<TString> tensorName, Operand<TString> shapeAndSlice, Class<T> dt,
      Options... options) {
    OperationBuilder opBuilder = scope.opBuilder(OP_NAME, "RestoreSlice");
    opBuilder.addInput(filePattern.asOutput());
    opBuilder.addInput(tensorName.asOutput());
    opBuilder.addInput(shapeAndSlice.asOutput());
    opBuilder.setAttr("dt", Operands.toDataType(dt));
    if (options != null) {
      for (Options opts : options) {
        if (opts.preferredShard != null) {
          opBuilder.setAttr("preferred_shard", opts.preferredShard);
        }
      }
    }
    return new RestoreSlice<>(opBuilder.build());
  }

  /**
   * Sets the preferredShard option.
   *
   * @param preferredShard Index of file to open first if multiple files match
   * {@code file_pattern}. See the documentation for {@code Restore}.
   * @return this Options instance.
   */
  public static Options preferredShard(Long preferredShard) {
    return new Options().preferredShard(preferredShard);
  }

  /**
   * Gets tensor.
   * The restored tensor.
   * @return tensor.
   */
  public Output<T> tensor() {
    return tensor;
  }

  @Override
  public Output<T> asOutput() {
    return tensor;
  }

  /**
   * Optional attributes for {@link org.tensorflow.op.train.RestoreSlice}
   */
  public static class Options {
    private Long preferredShard;

    private Options() {
    }

    /**
     * Sets the preferredShard option.
     *
     * @param preferredShard Index of file to open first if multiple files match
     * {@code file_pattern}. See the documentation for {@code Restore}.
     * @return this Options instance.
     */
    public Options preferredShard(Long preferredShard) {
      this.preferredShard = preferredShard;
      return this;
    }
  }

  @OpInputsMetadata(
      outputsClass = RestoreSlice.class
  )
  public static class Inputs extends RawOpInputs<RestoreSlice<?>> {
    /**
     * Must have a single element. The pattern of the files from
     * which we read the tensor.
     */
    public final Operand<TString> filePattern;

    /**
     * Must have a single element. The name of the tensor to be
     * restored.
     */
    public final Operand<TString> tensorName;

    /**
     * Scalar. The shapes and slice specifications to use when
     * restoring a tensors.
     */
    public final Operand<TString> shapeAndSlice;

    /**
     * The type of the tensor to be restored.
     */
    public final DataType dt;

    /**
     * Index of file to open first if multiple files match
     * {@code file_pattern}. See the documentation for {@code Restore}.
     */
    public final long preferredShard;

    public Inputs(GraphOperation op) {
      super(new RestoreSlice<>(op), op, Arrays.asList("dt", "preferred_shard"));
      int inputIndex = 0;
      filePattern = (Operand<TString>) op.input(inputIndex++);
      tensorName = (Operand<TString>) op.input(inputIndex++);
      shapeAndSlice = (Operand<TString>) op.input(inputIndex++);
      dt = op.attributes().getAttrType("dt");
      preferredShard = op.attributes().getAttrInt("preferred_shard");
    }
  }
}
